Whose thumb is it anyway?: classifying author personality from weblog text
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Beyond Microblogging: Conversation and Collaboration via Twitter
HICSS '09 Proceedings of the 42nd Hawaii International Conference on System Sciences
How and why people Twitter: the role that micro-blogging plays in informal communication at work
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Using linguistic cues for the automatic recognition of personality in conversation and text
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Tweet, Tweet, Retweet: Conversational Aspects of Retweeting on Twitter
HICSS '10 Proceedings of the 2010 43rd Hawaii International Conference on System Sciences
Social network use and personality
Computers in Human Behavior
Annotating named entities in Twitter data with crowdsourcing
CSLDAMT '10 Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk
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Predicting personality with social media
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HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Large scale personality classification of bloggers
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part II
Social network data and practices: the case of friendfeed
SBP'10 Proceedings of the Third international conference on Social Computing, Behavioral Modeling, and Prediction
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In this paper, we address the issue of how different personalities interact in Twitter. In particular we study users' interactions using one trait of the standard model known as the "Big Five": emotional stability. We collected a corpus of about 200000 Twitter posts and we annotated it with an unsupervised personality recognition system. This system exploits linguistic features, such as punctuation and emoticons, and statistical features, such as followers count and retweeted posts. We tested the system on a dataset annotated with personality models produced from human judgements. Network analysis shows that neurotic users post more than secure ones and have the tendency to build longer chains of interacting users. Secure users instead have more mutual connections and simpler networks.